How the brain represents duration remains an unsolved problem (Eagleman et al., 2005). It is clear that physical time does not have a direct mapping onto perceived time—instead, subjective duration judgments are surprisingly prone to distortions (Eagleman, 2008; Kanai et al, 2006; Morrone et al., 2005; Nakajima et al., 1992; Yarrow et al., 2001), such that two stimuli of identical duration can be perceived to last different amounts of time. For example, observers watching a repeated stimulus erroneously report that the first presentation (Kanai and Watanabe, 2006; Pariyadath and Eagleman, 2007; Rose and Summers, 1995) and any ‘oddball’ presentation (Pariyadath and Eagleman, 2007; Tse et al., 2004; Ulrich et al., 2006) appear longer in duration than the other presentations.
Although these duration illusions were originally suggested to be caused by increases in attention (Rose and Summers, 1995; Tse et al., 2004), it has been previously shown that the emotional salience of an oddball presentation has no effect on the illusion (Pariyadath and Eagleman, 2007), suggesting that the effect has more to do with the stimulus predictability than the amount of attentional deployment.
In flicker fusion experiments, a light is rapidly turned on and off: at a low frequency, flicker is perceived, while at a high frequency, the light appears to be steady. The frequency at which perception switches from flicker to a steady light is called the critical flicker fusion threshold (CFFT). CFFT experiments always consist of a single stimulus (the light) presented repeatedly. There are subjective duration differences when viewing familiar versus novel stimuli, thus, the inventors discovered that the CFFT would change if the rapid stimulus was made novel each time it appeared.
The perceived duration of novel and repeated stimuli map on to measured neural responses to the same (Grill-Spector et al., 2006). Normal human brains show diminishing responses to stimuli that are repeated over and over. This effect is known as repetition suppression (RS). In humans, these differential responses to familiar and novel stimuli are seen using electroencephalography (Grill-Spector et al., 2006), functional magnetic resonance imaging (Henson and Rugg, 2001), positron emission tomography (Buckner et al., 1995) and magnetoencephalography (Ishai et al., 2006). In non-human primates, the same phenomenon is observed by measuring the firing rates of individual neurons in higher cortical areas (Tahy et al., 1993; Rainer and Miller, 2000).
In some disorders, such as schizophrenia, RS is impaired, as evidenced by an impaired pre-pulse inhibition of the startle response (Hong et al., 2007), impaired mismatch negativity (Light and Braff, 2005), and abnormal processing of oddball stimuli (Kiehl and Liddle, 2001). Schizophrenic patients also have a lower sensitivity for detecting flicker (Black et al., 1975; Slaghuis and Bishop, 2001), which indicates that repeatedly flashed stimuli, which diminish in perceived duration in a normal brain, seem to last longer to a schizophrenic brain (Pariyadath and Eagleman, 2007). Collectively, these findings paint a picture of reduced or absent RS in schizophrenic patients. That is, to a schizophrenic brain, certain types of repeated stimuli will continue to appear novel. Presumably this reflects a deficit in cortical inhibition, which normally functions to provide RS (Daskalakis et al., 2002a; Daskalakis et al., 2002b). Further, data indicate that damage to the brain compromises performance on simple timing tasks. Therefore, measures of time perception, which are currently missing from the clinical landscape, are well-suited to provide a rapid and inexpensive way to screen for and rapidly identify traumatic brain injury (TBI). Currently used measures to highlight subtle brain damage (such as memory or cognition batteries) take a good deal of time and expertise to administer, rendering them ineffectual on the field. By contrast, simple timing tasks have the potential to highlight damage quickly and with no human administrator.
The measure of repetition suppression and visual persistence is a powerful diagnostic tool which can be used in the study of cognitive disorders. However, despite the increased knowledge that has been gained in recent years about the factors influencing repetition suppression, the basic measuring methodology has remained essentially unchanged. There is currently no method other than that disclosed here that allows inexpensive and rapid measurement of repetition suppression. Instead, all currently available methods use the technologies referred to in the studies above, namely, electroencephalography (Grill-Spector et al., 2006), functional magnetic resonance imaging (Henson and Rugg, 2001), positron emission tomography (Buckner et al., 1995) and magnetoencephalography (Ishai et al., 2006). These methods are uniformly expensive, time intensive, cause physical discomfort, necessitate training and expertise in administering the test, and require substantial data analysis. Therefore, there would be substantial interest in computer software or a physical device that could instantly and inexpensively yield an accurate measure of visual persistence and/or repetition suppression in human observers.